📄 Paper: "Clustering by fast search and find of density peaks"
👥 Authors: Alex Rodriguez and Alessandro Laio
🏛️ Journal: Science 344, 1492 (2014)
📈 Algorithm: Density Peaks Clustering (DPC)
🎯 Key Idea: Cluster centers are characterized by high density and large distance from points with higher density
Synthetic data with 5 density peaks of varying shapes and densities. Tests the algorithm's ability to detect non-spherical clusters with different densities.
Clustering Results
Shows the final clustering results. Different colors represent different clusters. Gray 'X' marks are halo/noise points. Yellow stars are cluster centers.
Decision Graph
Decision graph plotting δ (minimum distance to higher density point) vs ρ (local density). Cluster centers appear in the top-right corner (high δ and high ρ).
Gamma Values
Gamma values (γ = ρ × δ) sorted in descending order. Clear clusters show a sharp drop in γ values after the true centers.
Two crescent-shaped clusters (moons dataset). Tests ability to detect non-convex clusters.
Clustering Results
Shows the final clustering results. Different colors represent different clusters. Gray 'X' marks are halo/noise points. Yellow stars are cluster centers.
Decision Graph
Decision graph plotting δ (minimum distance to higher density point) vs ρ (local density). Cluster centers appear in the top-right corner (high δ and high ρ).
Gamma Values
Gamma values (γ = ρ × δ) sorted in descending order. Clear clusters show a sharp drop in γ values after the true centers.
15 highly overlapping Gaussian clusters. Tests resolution in distinguishing many clusters.
Clustering Results
Shows the final clustering results. Different colors represent different clusters. Gray 'X' marks are halo/noise points. Yellow stars are cluster centers.
Decision Graph
Decision graph plotting δ (minimum distance to higher density point) vs ρ (local density). Cluster centers appear in the top-right corner (high δ and high ρ).
Gamma Values
Gamma values (γ = ρ × δ) sorted in descending order. Clear clusters show a sharp drop in γ values after the true centers.
Three concentric circular clusters. Tests ability to detect nested structures.
Clustering Results
Shows the final clustering results. Different colors represent different clusters. Gray 'X' marks are halo/noise points. Yellow stars are cluster centers.
Decision Graph
Decision graph plotting δ (minimum distance to higher density point) vs ρ (local density). Cluster centers appear in the top-right corner (high δ and high ρ).
Gamma Values
Gamma values (γ = ρ × δ) sorted in descending order. Clear clusters show a sharp drop in γ values after the true centers.
Three curved, non-linearly separable clusters. Tests performance on complex shapes.
Clustering Results
Shows the final clustering results. Different colors represent different clusters. Gray 'X' marks are halo/noise points. Yellow stars are cluster centers.
Decision Graph
Decision graph plotting δ (minimum distance to higher density point) vs ρ (local density). Cluster centers appear in the top-right corner (high δ and high ρ).
Gamma Values
Gamma values (γ = ρ × δ) sorted in descending order. Clear clusters show a sharp drop in γ values after the true centers.
Side-by-side comparison of DPC algorithm performance on all test cases from Figure 3.
Algorithm Performance Comparison
Summary plot showing DPC clustering results on all four test cases from Figure 3.
Report generated: 2025-12-07 06:26:20